Prediction Audit: HB Koge vs Vejle Prediction, Odds & AI Betting Tips

Jul 31, 2026 - 17:00
0 1.29
2 1.31
xG Accuracy: 58%

AI correctly predicted the Vejle win.

The match finished 0–2, validating the model's directional assessment.

Tracked markets vs full-time result

Prediction grade B-

Each row compares the pre-match model lean to the full-time result.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Under 2.5 (2 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Vejle Vejle ✔ Correct
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 0-2 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Vejle higher than the statistical model.

Largest probability gap: Vejle -17.4 pp

Outcome Model Closing Market Difference Signal
HB Koge 34.7% 22.7% +12.0 pp Model Edge
Draw 29.6% 24.2% +5.4 pp Model Higher
Vejle 35.6% 53.1% -17.4 pp Market Higher

The closing market estimates Vejle's win probability at 53.1%, compared with the model's estimate of 35.6%, a difference of 17.4 percentage points. This highlights a disagreement between the model and market consensus, without indicating which view is ultimately correct.

Model probabilities are generated from the statistical xG model using a Poisson distribution. Closing market probabilities are derived from consensus closing 1X2 odds after margin removal. Values represent implied probabilities rather than betting recommendations. Closing snapshot: PRE1.

After full time, the model's directional lean matched the result (Vejle win 0–2).

Market Assessment

The market is materially more optimistic about Vejle than the current fair estimate.

  • Investors may be incorporating information not fully reflected in the baseline model.
  • Tournament-specific context can shift market pricing.

Post Match Insights

What worked

  • Under 2.5 goals aligned with the xG profile

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • Exact score: outside the model's top score bins

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Vejle higher (53.0% vs model 35.6%, 17.4 pp), but the model's lean was validated (Vejle win 0–2).

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Prediction Timeline

How this prediction moved from forecast to full-time review.

  1. Jul 31, 2026 · 17:01 UTC Forecast generated
    • Model 1X2 · HB Koge 34.7% · Draw 29.7% · Vejle 35.6%
    • xG · HB Koge 1.29 — Vejle 1.31
  2. Jul 31, 2026 · 16:31 UTC Opening odds snapshot PRE30
    • 1X2 odds · HB Koge 4.19 · Draw 3.92 · Vejle 1.79
    • Implied 1X2 · HB Koge 22.7% · Draw 24.2% · Vejle 53.1%
    • Bookmaker · Pinnacle
  3. Jul 31, 2026 · 17:01 UTC Closing snapshot recorded PRE1
    • 1X2 odds · HB Koge 4.19 · Draw 3.92 · Vejle 1.79
    • Implied 1X2 · HB Koge 22.7% · Draw 24.2% · Vejle 53.1%
    • Bookmaker · Pinnacle
  4. Jul 31, 2026 · 17:00 UTC Kickoff
  5. FT Full-time result Vejle win · 0–2
  6. FT Prediction validated Directional lean matched full-time result
  7. Archived Prediction review

Historical Snapshot

Frozen at kickoff — the model output as it stood before the match started.

Historical verdict: Monitor
Historical Decision Monitor
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 54/100 · Moderate
  • Validation: Warning
  • Large market gap (17 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 12/100
Betting Confidence 43/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 25, 2026 · 03:19 UTC Snapshot ID: dp-1673718

Closing Odds 1.79
AI Fair Odds —
CLV Pending
Final Result Vejle win · HB Koge 0–2 Vejle
Prediction ✔ Correct
Decision Grade B-

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

Review FAQ

How accurate was the prediction?
This page grades directional markets (1X2, Over/Under 2.5, BTTS) against the full-time result. The prediction grade reflects how many of those tracked markets matched reality.
What does xG Accuracy measure?
xG Accuracy compares the model's pre-match expected-goals profile to the actual scoreline — not whether every market hit. A strong directional review can coexist with a moderate xG accuracy score.
Why wasn't the exact score predicted?
Correct-score outcomes are low-probability tails even when the model reads the match profile well. We highlight top score bins for context; missing the exact line does not invalidate a directional review.
Does this improve the AI record?
Each finished match is logged in our validation pipeline. Aggregated hit rates and CLV studies are published separately — this page is the per-match audit trail.

Predictions are for informational purposes only. Always gamble responsibly and within your limits. Past performance does not guarantee future results.

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: 1. Division
  • Fixture: HB Koge vs Vejle
  • Kickoff: 2026-07-31 17:00:00
  • 1X2 (model): Home 34.7% · Draw 29.7% · Away 35.6%
  • xG (showing): HB Koge 1.29 — Vejle 1.31 (total xG ≈ 2.6)
  • Value headline: At least one tracked line reaches the headline EV threshold — align with the hero / Primary card if shown.
  • Structural leans (not bets): Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 51.8% · Over 2.5 48.2%); BTTS Yes (Yes 54.5% · No 45.5%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.6%)

When book depth is thin or odds are missing, EV may be unavailable even though the model still prefers one side on totals or BTTS — wait for cleaner prices or skip.

Most likely correct score stays a low-probability tail: use it for context, not as a must-bet story.

Historical Recommendation

Historical Decision: Monitor

Outcome: Validated — Pre-match lean validated against the full-time result.

Risk Factors Considered Before Kickoff

  • Price movement: implied probabilities and EV move with odds.
  • Sample / data gaps: low-information leagues widen forecast bands.
  • In-play state: goals and red cards are not modelled here.
  • Scoreline variance: the most likely scoreline is still usually a low absolute probability outcome (often well below 20%).

Last Updated

September 29, 2026 (UTC)

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Back to Predictions
1. Division 1. Division — Standings
# TEAM MP W D L PTS
1 Hvidovre 9 6 3 0 21
2 Vejle 9 5 4 0 19
3 FC Fredericia 9 3 5 1 14
4 Aarhus Fremad 9 3 4 2 13
5 Aalborg 9 3 4 2 13
6 Hobro 9 4 1 4 13
7 Vendsyssel FF 9 2 4 3 10
8 AB Copenhagen 9 2 3 4 9
9 Hillerød 9 2 3 4 9
10 Kolding IF 9 1 5 3 8
11 HB Koge 9 1 4 4 7
12 Esbjerg 9 1 2 6 5
# TEAM MP GS GC +/- PTS
1 Vejle 9 22 13 +9 19
2 Hvidovre 9 18 9 +9 21
3 Hillerød 9 13 14 -1 9
4 FC Fredericia 9 12 6 +6 14
5 Hobro 9 12 16 -4 13
6 AB Copenhagen 9 11 10 +1 9
7 Aalborg 9 11 11 0 13
8 HB Koge 9 11 17 -6 7
9 Aarhus Fremad 9 10 9 +1 13
10 Kolding IF 9 10 12 -2 8
11 Vendsyssel FF 9 10 14 -4 10
12 Esbjerg 9 10 19 -9 5